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PurposeThe transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.Design/methodology/approachThis study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.FindingsThe results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders' environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.Research limitations/implicationsDespite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).Practical implicationsAccording to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.Originality/valueThis study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

Traffic congestion in metropolitan areas all over the world has become a critical issue that governments mustdeal with effectively. Traffic congestion during rush hours causes vehicle drivers to arrive late at their destinations,resulting in significant economic losses. Although researchers have proposed solutions to the traffic congestionproblem, little research work has presented a joint route and charging planning strategy for electric vehicles(EVs) that alleviates traffic congestion problems simultaneously. Accordingly, a congestion-preventing route and charging planning mechanism for EVs is proposed in this work to tackle the complicated route and charging optimizationproblems of EVs. The route and charging planning proposed in this work analyzes the information providedby EVs, the charging points, and road traffic information simultaneously, and mediates the traffic jammingby means of a route and charging reservation mechanism. Possible occurrence of traffic congestion is detectedin advance and traffic regulation is carried out by allocating an elastic range to the traveling period for late-bookingEVs, to avoid moving during rush hours. EV owners are also encouraged to provide rideshare services forlate-booking EV users during rush hours. The simulation results reveal that the proposed work can satisfy thepreferred route and charging demands of EV users and alleviate traffic congestion effectively.

The association of VEGF+405G/C (where VEGF is vascular endothelial growth factor) polymorphism and malignancy susceptibility attracts considerable attention because VEGF is one of the most potent angiogenic factors and plays a critical role in the onset and development of malignancy. However, the published findings remain inconclusive. In order to derive a more precise assessment of the association, we performed a meta-analysis including 30 published case-control studies from PubMed, Embase, and Ovid databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the association. In the pooled analyses, no significant association was found between VEGF+405G/C polymorphism and malignancy susceptibility in different genetic models (G-allele vs. C-allele: OR = 1.00, 95% CI: 0.93–1.07; CC vs. GG: OR = 1.01, 95% CI: 0.88–1.15; GC+CC vs. GG: OR = 1.00, 95% CI: 0.91–1.10; CC vs. GC+GG: OR = 1.01, 95% CI: 0.90–1.13). When stratified by ethnicity, a weak association between this polymorphism and malignancy susceptibility was found in African under allelic frequency comparison (OR = 0.65, 95% CI: 0.43–0.98) and dominant genetic model comparison (OR = 1.95, 95% CI: 1.09–3.50). In summary, although our meta-analysis indicated a weak association of VEGF+405G/C polymorphism with malignancy susceptibility in African, no persuasive evidence of association between the polymorphism and malignancy susceptibility was detected in the pooled analyses. Therefore, more studies with larger scale of participants, especially Africans, are required to further evaluate gene-environment interaction on this polymorphism and malignancy susceptibility.

The operation and planning of power systems depend heavily on M-LTLF, which is complicated and nonlinear, making it challenging for conventional medium- and long-term forecasting models to produce reliable results. The SARIMA model is chosen for M-LTLF in this study, and the model's parameters are tuned. This study takes the electricity consumption data of the whole Yunnan as the research object. Among them, the electricity consumption data from 2008 to 2018 is used as a training sample for fitting and analysis, and the electricity consumption of the whole province is predicted from 2019 to 2020. The end results demonstrate the viability and efficacy of the SARIMA model for M-LTLF.

AbstractThis study explores key critical factors of waterfront port development (WPD) by applying analytic network process (ANP) and analytic hierarchy process (AHP) to the Incheon and Bangkok ports, drawing certain implications. The major findings of this paper show that the ANP draws more stable, comprehensive, and consistent results than the AHP, and the ANP ranking results of the three cases, showed four common key critical criteria of WPD exist among the top five (i.e., accessibility under community function; connectivity under port function; maritime clustering, and transformation of the port/city interface under economic function).

In order to predict China's electricity consumption demand under situation of fast growth of the new infrastructure, a medium- and long-term electricity consumption demand prediction model based on LEAP is proposed, which calculates the overall electricity consumption of the country according to the activity level and intensity of typical new infrastructure and other sectors. Five different scenarios are set for comparison. The results show that under the basic scenario, China's electricity consumption will reach 7408 billion kWh in 2035, in which the consumption of new infrastructure accounts for 31.31%.While under the other four scenarios, China's electricity consumption will reach to the minimum of 7319 billion kWh under the scenario of improvement of energy-saving technology, and the maximum of 7525 billion kWh under the scenario of fast development of the new infrastructure, with higher contributions of the consumption of commercial charging, data centers and 5G base station. Relevant suggestions are put forward from the aspects of new infrastructure construction, development of clean energy and technical standards to reduce the electricity consumption of new infrastructure.